The skew spectrum of graphs Risi Kondor
Gatsby Unit, UCL with
Karsten Borgwardt
University of Cambridge
Can just 49 features characterize a graph?
up to ~300 vertices
2 3 1
4 5
7
0 0 0 A= 1 0 0 0
0 0 1 1 0 0 0
0 1 0 1 0 0 0
1 1 1 0 0 1 0
0 0 0 0 0 1 0
0 0 0 1 1 0 1
0 0 0 0 0 1 0
6
q(A) is a graph invariant if it is invariant to relabeling.
poly(n) time computable
complete set of invariants Graph isomorphism problem
efficiently computable set of invariant features Graph kernels, etc.
0 1 0 0 1 0 1 1 0 1 0 1 0 1 1 0
!→
v
π
=
P (π) ⊗ P (π)
[P (π)]i,j =
!
1 0
· v
if π(j) = i otherwise
! q = v v Our first invariant: 0
Ov
π
=
ρ1 (π)
ρ2 (π)
ρ3 (π)
· Ov
P (π) ⊗ P (π) = ρ1 (σ) ⊕ ρ2 (σ) ⊕ . . . ⊕ ρk (σ)
Now we have a whole bunch of invariants: q1 =
! v1 v1 ,
q2 =
! v2 v2 ,
. . . , qm =
! vk vk
f!(ρ) =
"
f (σ) ρ(σ)
σ∈Sn
ρ(σ2 σ1 ) = ρ(σ2 ) ρ(σ1 ) representation
f!(ρ) =
"
f (σ) ρ(σ)
σ∈Sn
• Ivertible • Unitary π −1 theorem • Translation f (σ) = f (π σ) • Convolution theorem • etc.
π ! f (ρ) = ρ(π) · f!(ρ)
•
f!(ρ) =
"
f (σ) ρ(σ)
σ∈Sn
Diaconis: Group representations in probability and statistics (1988) • Clausen, Maslen, Rockmore, Healy, ... : FFTs • Kondor, Howard and Jebara: Multi-object tracking with representations of the symmetric group (AISTATS, 2007) • Huang, Guestrin and Guibas: Efficient inference for distributions on permutations (NIPS, 2007)
The Fourier spectrum of graphs
f (σ) = [A]σ(n),σ(n−1) f!(ρ)
!→
! ! ! f (ρ) · f (ρ)
ρ(π) f!(ρ) invariant
Example ρ1 (σ) =
For σ = (1, 2, 3, 4, 5) ∈ S5 !
1
"
−0.5 0.866 ρ2 (σ) = 0 0
ρ3 (σ) =
ρ4 (σ) =
−0.289 −0.167 0.943 0
−0.204 −0.118 −0.0833 0.968
0.25 −0.433 −0.433 −0.25 −0.433 −0.25 0.75 −0.144 0 0.816
0.333 0.236 −0.471 0.0417 0.816 −0.0722 0 −0.484 0 0.839 0 0
−0.791 −0.456 −0.323 −0.25
0.433 −0.75 0.25 −0.433 0
0 0.217 0.125 −0.28 −0.161 0.913
−0.75 −0.433 0.144 0.0833 −0.471
0.913 0.161 −0.28 0.125 −0.217 0
0 0 −0.816 −0.471 −0.333
0 0 0.839 0 0.484 0 0.0722 0.816 0.0417 0.471 −0.236 0.333
Example f!(ρ1 ) = (6)
-0.25 -0.323 f!(ρ2 ) = 0.913 0 1.33 0.471 f!(ρ3 ) = 0 0.816 0
! f (ρ4 ) =
-1.67 1.18 0 -0.913 0 -2.24
-0.323 -0.417 1.18 0
0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0
0 0 0 0
0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0
0 0 0 0
0 0 0 0 0 0
Ov
π
=
ρ1 (π)
ρ2 (π)
ρ3 (π)
· Ov
Now we have a whole bunch of invariants: q1 =
! v1 v1 ,
q2 =
! v2 v2 ,
. . . , qm =
! vk vk
Example f!(ρ1 ) = (6)
-0.25 -0.323 f!(ρ2 ) = 0.913 0 1.33 0.471 f!(ρ3 ) = 0 0.816 0
! f (ρ4 ) =
-1.67 1.18 0 -0.913 0 -2.24
-0.323 -0.417 1.18 0
0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0
0 0 0 0
0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0
0 0 0 0
0 0 0 0 0 0
... but there is more ...
!
$ #! f"(ρ1 ) ⊗ f"(ρ2 ) Cρ1 ,ρ2 f"(ρ) ρ
non-commutative bispectrum [Kakarala ’92]
Skew spectrum q!ν (ρ) = r!ν (ρ) · f!(ρ) !
rν (σ) = f (σπ)f (σ)
Just 7 ν values!
[Kondor, 2007]
Sn
Bratelli diagram
http://www.gatsby.ucl.ac.uk/~risi/SnOB
49 graph invariants computable in
O(n ) 3
time
Number of instances/classes Max. number of nodes Reduced skew spectrum Random walk kernel Shortest path kernel
MUTAG 600/6 28 88.61 (0.21) 71.89 (0.66) 81.28 (0.45)
ENZYME 188/2 126 25.83 (0.34) 14.97 (0.28) 27.53 (0.29)
NCI1 4110/2 111 62.72 (0.05) 51.30 (0.23) 61.66 (0.10)
NCI109 4127/2 111 62.62 (0.03) 53.11 (0.11) 62.35 (0.13)
•
A general method for generating invariants
•
Only 49 graph invariants, but surprisingly powerful
•
Very fast to compute
•
Next: labeled graphs
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